The machining of a part from raw stock or material, usually metal, is a form of subtractive manufacturing during which the raw material is progressively removed until the part reaches an intended shape and size. Operations during machining primarily involve turning, drilling and milling the raw material into the desired part, which respectively require removing the raw material by rotating the raw material against a stationary cutting tool, axially boring holes using a rotating bit with a cutting edge on a distal end whilst the raw material is held stationary, and cutting away the raw material using a rotating bit with cutting edges generally along the rotating bit's sides and distal end. Both drilling and milling involve traversing a rotating bit along a longitudinal axis in the Z-direction. Milling, which operates in three-dimensional space, also involves moving the rotating bit along a plane in X- and Y-directions. Other kinds of machining operations and tools also exist. The machining will generally reduce the raw material into rough form within a specified tolerance; further manufacturing processes may be required to smooth, polish, finish, or otherwise transform the part into final form.
As with other facets of product lifecycle management, machining has benefited from increased integration of computerization. For instance, digitally-automated milling machines can be programmed to manufacture parts from raw materials using computer numerical control (CNC) machining instructions, which are typically generated through computer-aided manufacturing (CAM) software based on user-driven inputs combined with automated post-planning process validation. The part is digitally represented through an electronically-stored model output from a computer-aided design (CAD) program, and the CAM software uses the part's digital model, along with a model of the manufacturing setup, including the machining tools, to create the set of machining instructions.
Despite the advances in parts design and manufacture made possible by CAD, CAM and related digital manufacturing software initiatives, conventional efforts still focus primarily on assisting validation of human-generated manufacturing process plans in an effort to better support efficient integration between product lifecycle management and physical shop floor production. In general, these software initiatives provide virtual environments that enable modeling, planning, simulation, and analysis of manufacturing processes, as supported by algorithms for path planning, collision detection, cycle time calculations, layout modeling and resource allocation, and validate user-driven inputs, ranging from a single operation to an entire manufacturing program.
Nevertheless, a problem remains in synthesizing a manufacturing process plan that defines a sequence of machining instructions, such as expressible in a CNC program, to produce a part from raw stock. Depending on part complexity, addressing this problem manually and without automation may be a time-consuming and expensive effort. Moreover, the exercise can potentially occupy a large segment of the process planning stage and will invariably require human intervention, creativity and experience to sufficiently define the process before its execution may be validated with a suite of digital manufacturing tools.
The inverse problem, that of defining a process plan for manufacturing a mechanical part through digitally-automated machining, is likewise ill-posed, for there are typically multiple solutions, with the space of solutions growing with the increasing geometric complexity of the part and the availability of a larger set of machining tools. Furthermore, process plans are influenced by machine-specific parameters, setup and manufacturing time and costs, design tolerances, layout planning, and so forth. The solution space becomes intractable and lacks process-driven feedback that could guide manufacturability analysis and process planning selection. Conventional solutions to producing manufacturing process plans for parts with arbitrary geometric complexity fail to resolve these problems.
For instance, W. Fu et al., “A Graph Grammar Based Approach to Automated Manufacturing Planning,” Proc. ASME 2012 Int'l Design Engr. Tech. Confs. & Comps. And Info. In Engr. Conf. (Aug. 12-15, 2012), the disclosure of which is incorporated by reference, describes a graph grammar representation for reasoning about parts manufacturability. A part is decomposed into multiple sub-volumes with each sub-volume assumed to either be machinable in one operation or non-machinable. The decomposed part is converted into a graph and a candidate manufacturing plan is generated as a sequence of all machining operations necessary to manufacture the part based on the assumptions that the sub-volumes are machinable. However, dependence on part decomposition restricts the class of parts considered manufacturable, and the graph grammar approach relies on heuristics whose application dramatically increases the solution space that must be explored, which considerably slows down the evaluation of manufacturability.
Therefore, a need remains for an approach to validating whether a designed part is fundamentally manufacturable and, if so, through what sequence of manufacturing process plans.